AI & RAG
Security Questionnaire Batch Responder Grounded in Evidence Corpus
Takes an inbound vendor security questionnaire row by row from a Supabase queue, answers each item from the frozen evidence corpus with citations.
How it runs
The automated pipeline, trigger to output.
- TriggerNew questionnaire batch enqueued in SupabaseSupabase
- ActionRead pending items and embed each questionSupabase
- ActionRetrieve supporting clauses from pgvector corpusPostgres
- ActionDraft cited answer per itemOpenAI
- LogicFlag low-confidence items as needs-review
- OutputWrite drafts, citations, and flags back to SupabaseSupabase
What it does
Automates first-pass responses to vendor and customer security questionnaires. Each questionnaire item is pulled from a Supabase queue, matched against the frozen evidence corpus, and answered with a grounded draft and a citation to the supporting clause. Low-confidence items are flagged so a human reviewer only touches the questions the corpus can't fully cover.
When to use it
When your team faces long recurring questionnaires (CAIQ, SIG, custom vendor forms) and wants AI to draft cited answers for the routine 80% while clearly marking what still needs a human.
How it works
- 1A new questionnaire batch lands in the Supabase queue and triggers processing.
- 2Each pending item is read and embedded, then matched to corpus clauses in pgvector.
- 3OpenAI drafts an answer per item, constrained to the retrieved evidence, with a citation.
- 4A confidence check tags each draft as auto-fillable or needs-review.
- 5Drafts, citations, and review flags are written back to the Supabase questionnaire table.
Set it up
What you configure once, before turning it on.
- 1Connect SupabaseTables, auth, storage, edge functions.
- 2Connect PostgresAny Postgres URL — query, write, migrate.
- 3Connect OpenAIModels, embeddings, files.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
More AI & RAG workflows
Coda-grounded sales answer bot with citations in Slack
Reps ask product, pricing, or competitive questions in Slack and get an answer drawn only from your Coda knowledge hub, with links to the exact docs and rows it pulled from.
Weekly knowledge-gap digest from unanswered rep questions
Each week, scans rep questions the answer bot couldn't ground in Coda, clusters the recurring gaps.
Pre-meeting prep brief grounded in Coda and CRM
Before each booked sales meeting, builds a one-page prep brief by combining the account's HubSpot context with grounded talking points and objection responses pulled from your…
Publish a Grounded API FAQ Page to Confluence Weekly
Each week, clusters the top unanswered or repeated API questions, generates spec-grounded answers with citations.
Detect Breaking API Changes from Spec Diffs and Alert Owners
Compares the new OpenAPI spec against the previous version on each GitLab merge, uses retrieval over the changelog to classify whether changes are breaking.
Re-Index API Specs on GitLab Merge to Keep the Answer Bot Fresh
Watches GitLab merges to your API repo, detects changed OpenAPI specs and changelog files, re-chunks and re-embeds only what changed.
Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
Run this workflow in your colony.
14-day trial. No DevOps. No Sales call. Provisioned in under a minute.